Learning Multilingual Word Embeddings Using Image-Text Data. - Karan Singhal; Karthik Raman 001; Balder ten Cate (CoRR, 2019)

Federated Reconstruction: Partially Local Federated Learning. - Karan Singhal; Hakim Sidahmed; Zachary Garrett; Shanshan Wu; John Rush; Sushant Prakash (NeurIPS, 2021)

Federated Reconstruction: Partially Local Federated Learning. - Karan Singhal; Hakim Sidahmed; Zachary Garrett; Shanshan Wu; Keith Rush; Sushant Prakash (CoRR, 2021)

A Field Guide to Federated Optimization. - Jianyu Wang; Zachary Charles; Zheng Xu 002; Gauri Joshi; H. Brendan McMahan; Blaise Agüera y Arcas; Maruan Al-Shedivat; Galen Andrew; Salman Avestimehr; Katharine Daly; Deepesh Data; Suhas N. Diggavi; et al. (CoRR, 2021)

Learning Federated Representations and Recommendations with Limited Negatives. - Lin Ning 001; Karan Singhal; Ellie X. Zhou; Sushant Prakash (CoRR, 2021)

What Do We Mean by Generalization in Federated Learning? - Honglin Yuan 002; Warren Richard Morningstar; Lin Ning 001; Karan Singhal (ICLR, 2022)

Mixed Federated Learning: Joint Decentralized and Centralized Learning. - Sean Augenstein; Andrew Hard; Lin Ning 001; Karan Singhal; Satyen Kale; Kurt Partridge; Rajiv Mathews (CoRR, 2022)

Plex: Towards Reliability using Pretrained Large Model Extensions. - Dustin Tran; Jeremiah Z. Liu; Michael W. Dusenberry; Du Phan; Mark Collier; Jie Ren 006; Kehang Han; Zi Wang; Zelda Mariet; Huiyi Hu; Neil Band; Tim G. J. Rudner; et al. (CoRR, 2022)

Federated Training of Dual Encoding Models on Small Non-IID Client Datasets. - Raviteja Vemulapalli; Warren Richard Morningstar; Philip Andrew Mansfield; Hubert Eichner; Karan Singhal; Arash Afkanpour; Bradley Green (CoRR, 2022)

Large Language Models Encode Clinical Knowledge. - Karan Singhal; Shekoofeh Azizi; Tao Tu 001; S. Sara Mahdavi; Jason Wei; Hyung Won Chung; Nathan Scales; Ajay Kumar Tanwani; Heather Cole-Lewis; Stephen Pfohl; Perry Payne; Martin Seneviratne; et al. (CoRR, 2022)

Random field augmentations for self-supervised representation learning. - Philip Andrew Mansfield; Arash Afkanpour; Warren Richard Morningstar; Karan Singhal (NeurReps, 2023)

Towards Expert-Level Medical Question Answering with Large Language Models. - Karan Singhal; Tao Tu 001; Juraj Gottweis; Rory Sayres; Ellery Wulczyn; Le Hou; Kevin Clark; Stephen Pfohl; Heather Cole-Lewis; Darlene Neal; Mike Schaekermann; Amy Wang; et al. (CoRR, 2023)

Towards Generalist Biomedical AI. - Tao Tu 001; Shekoofeh Azizi; Danny Driess; Mike Schaekermann; Mohamed Amin; Pi-Chuan Chang; Andrew Carroll; Chuck Lau; Ryutaro Tanno; Ira Ktena; Basil Mustafa; Aakanksha Chowdhery; et al. (CoRR, 2023)

Towards Federated Learning Under Resource Constraints via Layer-wise Training and Depth Dropout. - Pengfei Guo; Warren Richard Morningstar; Raviteja Vemulapalli; Karan Singhal; Vishal M. Patel; Philip Andrew Mansfield (CoRR, 2023)

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation. - Ryutaro Tanno; David G. T. Barrett; Andrew Sellergren; Sumedh Ghaisas; Sumanth Dathathri; Abigail See; Johannes Welbl; Karan Singhal; Shekoofeh Azizi; Tao Tu 001; Mike Schaekermann; Rhys May; et al. (CoRR, 2023)

Towards Accurate Differential Diagnosis with Large Language Models. - Daniel McDuff; Mike Schaekermann; Tao Tu 001; Anil Palepu; Amy Wang; Jake Garrison; Karan Singhal; Yash Sharma; Shekoofeh Azizi; Kavita Kulkarni; Le Hou; Yong Cheng; et al. (CoRR, 2023)

Towards Conversational Diagnostic AI. - Tao Tu 001; Anil Palepu; Mike Schaekermann; Khaled Saab 003; Jan Freyberg; Ryutaro Tanno; Amy Wang; Brenna Li; Mohamed Amin; Nenad Tomasev; Shekoofeh Azizi; Karan Singhal; et al. (CoRR, 2024)

Augmentations vs Algorithms: What Works in Self-Supervised Learning. - Warren R. Morningstar; Alex Bijamov; Chris Duvarney; Luke Friedman; Neha Mukund Kalibhat; Luyang Liu; Philip Andrew Mansfield; Renan A. Rojas-Gomez; Karan Singhal; Bradley Green; Sushant Prakash (CoRR, 2024)

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. - Stephen R. Pfohl; Heather Cole-Lewis; Rory Sayres; Darlene Neal; Mercy Nyamewaa Asiedu; Awa Dieng; Nenad Tomasev; Qazi Mamunur Rashid; Shekoofeh Azizi; Negar Rostamzadeh; Liam G. McCoy; Leo Anthony Celi; et al. (CoRR, 2024)

SASSL: Enhancing Self-Supervised Learning via Neural Style Transfer. - Renan A. Rojas-Gomez; Karan Singhal; Ali Etemad; Alex Bijamov; Warren Richard Morningstar; Philip Andrew Mansfield (Trans. Mach. Learn. Res., 2024)

Federated Variational Inference: Towards Improved Personalization and Generalization. - Elahe Vedadi; Joshua V. Dillon; Philip Andrew Mansfield; Karan Singhal; Arash Afkanpour; Warren Richard Morningstar (Trans. Mach. Learn. Res., 2024)

Disentangling the Effects of Data Augmentation and Format Transform in Self-Supervised Learning of Image Representations. - Neha Mukund Kalibhat; Warren Richard Morningstar; Alex Bijamov; Luyang Liu; Karan Singhal; Philip Andrew Mansfield (UniReps, 2025)

Enhancing User Sequence Modeling through Barlow Twins-based Self-Supervised Learning. - Yuhan Liu; Lin Ning 001; Neo Wu; Karan Singhal; Philip Andrew Mansfield; Devora Berlowitz; Sushant Prakash; Bradley Green (CoRR, 2025)

HealthBench: Evaluating Large Language Models Towards Improved Human Health. - Rahul K. Arora; Jason Wei; Rebecca Soskin Hicks; Preston Bowman; Joaquin Quiñonero Candela; Foivos Tsimpourlas; Michael Sharman; Meghan Shah; Andrea Vallone; Alex Beutel; Johannes Heidecke; Karan Singhal (CoRR, 2025)

AI-based Clinical Decision Support for Primary Care: A Real-World Study. - Robert Korom; Sarah Kiptinness; Najib Adan; Kassim Said; Catherine Ithuli; Oliver Rotich; Boniface Kimani; Irene King'ori; Stellah Kamau; Elizabeth Atemba; Muna Aden; Preston Bowman; et al. (CoRR, 2025)

gpt-oss-120b & gpt-oss-20b Model Card. - Sandhini Agarwal; Lama Ahmad; Jason Ai; Sam Altman; Andy Applebaum; Edwin Arbus; Rahul K. Arora; Yu Bai; Bowen Baker; Haiming Bao; Boaz Barak; Ally Bennett; et al. (CoRR, 2025)